PREDICTION OF NON-NATIVE INVASIVE PLANT SPECIES OCCURRENCES IN RELATION TO ENVIRONMENTAL VARIABLES IN SOUTHERN ILLINOIS

Author

xian liu, Southern Illinois University CarbondaleFollow

Date of Award

6-1-2021

Degree Name

Doctor of Philosophy

Department

Environmental Resources & Policy

First Advisor

Gibson, David

Second Advisor

Wang, Guangxing

Abstract

Non-native invasive plants are destructive plants brought into places where they did occur before naturally. The rapid spread of non-native invasive plants has become an urgent threat to ecosystems at a global scale, and it is a top priority problem for natural resources management. The overall objective of this project is to predict the occurrence of some common non-native invasive plants species in Southern Illinois to allow management policies to be developed.Seventeen of the most common and abundant non-native invasive species in Southern Illinois were analyzed. Eleven environmental variables were used to model species distributions and estimate their importance to species distributions. Results showed that land cover and soil (major land resource area) were the two most significant variables related to most of focal species distributions and made the most contributions in this study. Prediction maps indicated that most species had high probabilities of occurrence at the central south and along the riversides of the Southern Illinois area. To explore how climate change affects species invasions and habitats, an ensemble of 5 commonly used atmosphere-ocean general circulation models (AOGCMs) (CanESM2, CCSM 4.0, CGCM3.0, CSIRO MK3.5, and NorESM) were used to project future climate conditions. Overall, land cover and soil types (major land resource area) were the two most significant non-climate variables related to most of focal species distributions. Species with a narrow habitat or which preferred specific habitats would be mostly affected by land cover types and soil types while species (e.g., Lonicera maackii) having wide habitat tolerance would be least impacted. Prediction maps showed that most species had distribution trends from east to west in the central south area or from central south to north east. The center of the southern part of the area dominated by the Shawnee National Forest was predicted to have the most suitable habitats for all focal species except for Humulus japonicus and Phragmites australis. The predicted distributions under climate scenarios indicated that species distributions could change or shift under different representative concentration pathways (RCPs) and potential suitable habitat might expand under climate change. Change detection was conducted to quantitatively examine how changing climate could affect invasive species’ potential habitats. The five species with the most species records were evaluated for this analysis. For these species, potential suitable habitats were most likely to expand in the central west of study area for all climate change scenarios. Species suitable habitats would shift under climate change. Functional group and phylogenetic group analyses were conducted to investigate how species groups affect species spatial distributions and how evolutionary related nonnative invasive species distribute spatially. The 17 focal species were grouped into 4 broad functional groups (Woody and shrub species -FG1, herbaceous species -FG2, grass species -FG3, and vine species -FG4) based on life form. AUC indicated that model performance of functional groups was no better than of individual species alone. Land cover was the variable with the largest variable contribution to the predicted distributions of FG1, FG3, and FG4 while maximum temperature had the largest contribution for FG2. Composite maps for the functional groups showed that the central south dominated by the Shawnee National Forest was predicted as the most suitable habitats for all four functional groups. The composite maps for these functional groups were similar to the maps for the individual species within each own functional group. Genetic sequences of each species were used to construct a phylogeny. Besides the 17 focal species, an outgroup species Berberis vulgaris was added into the model to root the phylogenetic tree. Based on the resulting phylogenetic tree, species were classed into 3 groups (superasterids-PG1, monocots-PG2, and superrosids-PG3) based phylogenetic relativeness and distance. AUC indicated that model performance of phylogenetic groups was no better than of individual species alone. Variable contributions of functional groups indicated that landcover was the most significant variable for all three PGs. Composite maps showed the central south was predicted as hotspot. Phylogenetically related species responded similarly to the single species. This study focused on the prediction of non-native invasive species distributions in relation to environmental variables. Environmental factors that significantly affect invasive species distributions can indicate natural resource managers when conducting invasive species management is necessary. The approach of studying how invasive species respond to climate change can be extended to other invasive species research. By integrating functional groups and phylogenetic groups into species distribution predictions, species with too few records for modeling can be examined with abundant species in the same functional or phylogenetic group in predicting distributions. However, this research did not study how interspecific interactions (i.e, competition) between native and invasive species would affect species invasion. Further research of intergrating biotic factors is needed.